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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

MassIVE MSV000094089

GNPS - Determination of metabolic changes occurring in engineered low-lignin poplar

Aromatics↗
DOE OSTI2024

The contribution of BvgR, RisA, and RisS to global gene regulation, intracellular cyclic-di-GMP levels, motility, and biofilm formation in Bordetella bronchiseptica

Bordetella bronchiseptica is a highly contagious respiratory bacterial veterinary pathogen. In this study the contribution of the transcriptional regulators BvgR, RisA, RisS, and the phosphorylation of RisA to global gene regulation, intracellular cyclic-di-GMP levels, motility, and biofilm formation were evaluated. Next Generation Sequencing (RNASeq) was used to differentiate the global gene regulation of both virulence-activated and virulence-repressed genes by each of these factors. The BvgAS system, along with BvgR, RisA, and the phosphorylation of RisA served in cyclic-di-GMP degradation. BvgR and unphosphorylated RisA were found to temporally regulate motility. Additionally, BvgR, RisA, and RisS were found to be required for biofilm formation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Transcriptome analysis and immune gene expression of channel catfish ( Ictalurus punctatus ) fed diets with inclusion of frass from black soldier fly larvae

The larval waste, exoskeleton shedding, and leftover feed components of the black soldier fly and its larvae make up the by-product known as frass. In this study, we subjected channel catfish (Ictalurus punctatus) to a 10-week feeding trial to assess how different dietary amounts of frass inclusion would affect both systemic and mucosal tissue gene expression, especially in regard to growth and immune-related genes. Fish were divided in quadruplicate aquaria, and five experimental diets comprising 0, 50, 100, 200, and 300 g of frass per kilogram of feed were fed twice daily. At the end of the trial, liver, head kidney, gill, and intestine samples were collected for gene expression analyses. First, liver and intestine samples from fish fed with a no frass inclusion diet (control), low-frass (50 g/kg) inclusion diet, or a high-frass (300 g/kg) inclusion diet were subjected to Illumina RNA sequencing to determine global differential gene expression among diet groups. Differentially expressed genes (DEGs) included the upregulation of growth-related genes such as glucose-6-phosphatase and myostatin, as well as innate immune receptors and effector molecules such as toll-like receptor 5, apolipoprotein A1, C-type lectin, and lysozyme. Based on the initial screenings of low/high frass using RNA sequencing, a more thorough evaluation of immune gene expression of all tissues sampled, and all levels of frass inclusion, was further conducted. Using targeted quantitative PCR panels for both innate and adaptive immune genes from channel catfish, differential expression of genes was identified, which included innate receptors (TLR1, TLR5, TLR9, and TLR20A), proinflammatory cytokines (IL-1β type a, IL-1β type b, IL-17, IFN-γ, and TNFα), chemokines (CFC3 and CFD), and hepcidin in both systemic (liver and head kidney) and mucosal (gill and intestine) tissues. Overall, frass from black soldier fly larvae inclusion in formulated diets was found to alter global gene expression and activate innate and adaptive immunity in channel catfish, which has the potential to support disease resistance in this species in addition to demonstrated growth benefits.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Biological insights from multi-omics analysis strategies: Complex pleotropic effects associated with autophagy

Research strategies that combine molecular data from multiple levels of genome expression (i.e., multi-omics data), often referred to as a systems biology strategy, has been advocated as a route to discovering gene functions. In this study we conducted an evaluation of this strategy by combining lipidomics, metabolite mass-spectral imaging and transcriptomics data from leaves and roots in response to mutations in two AuTophaGy-related ( ATG ) genes of Arabidopsis . Autophagy is an essential cellular process that degrades and recycles macromolecules and organelles, and this process is blocked in the atg7 and atg9 mutants that were the focus of this study. Specifically, we quantified abundances of ~100 lipids and imaged the cellular locations of ~15 lipid molecular species and the relative abundance of ~26,000 transcripts from leaf and root tissues of WT, atg7 and atg9 mutant plants, grown either in normal (nitrogen-replete) and autophagy-inducing conditions (nitrogen-deficient). The multi-omics data enabled detailed molecular depiction of the effect of each mutation, and a comprehensive physiological model to explain the consequence of these genetic and environmental changes in autophagy is greatly facilitated by the a priori knowledge of the exact biochemical function of the ATG7 and ATG9 proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Morpho-physiological and transcriptomic responses of field pennycress to waterlogging

Field pennycress (Thlaspi arvense) is a new biofuel winter annual crop with extreme cold hardiness and a short life cycle, enabling off-season integration into corn and soybean rotations across the U.S. Midwest. Pennycress fields are susceptible to winter snow melt and spring rainfall, leading to waterlogged soils. The objective of this research was to determine the extent to which waterlogging during the reproductive stage affected gene expression, morphology, physiology, recovery, and yield between two pennycress lines (SP32-10 and MN106). In a controlled environment, total pod number, shoot/root dry weight, and total seed count/weight were significantly reduced in SP32-10 in response to waterlogging, whereas primary branch number, shoot dry weight, and single seed weight were significantly reduced in MN106. This indicated waterlogging had a greater negative impact on seed yield in SP32-10 than MN106. We compared the transcriptomic response of SP32-10 and MN106 to determine the gene expression patterns underlying these different responses to seven days of waterlogging. The number of differentially expressed genes (DEGs) between waterlogged and control roots were doubled in MN106 (3,424) compared to SP32-10 (1,767). Functional enrichment analysis of upregulated DEGs revealed Gene Ontology (GO) terms associated with hypoxia and decreased oxygen, with genes in these categories encoding proteins involved in alcoholic fermentation and glycolysis. Additionally, downregulated DEGs revealed GO terms associated with cell wall biogenesis and suberin biosynthesis, indicating suppressed growth and energy conservation. Interestingly, MN106 waterlogged roots exhibited significant stronger regulation of these genes than SP32-10, displaying a more robust transcriptomic response overall. Together, these results reveal the reconfiguration of cellular and metabolic processes in response to the severe energy crisis invoked by waterlogging in pennycress.

ERF-VII↗
DOE OSTI2021

Evidence for Lignocellulose-Decomposing Enzymes in the Genome and Transcriptome of the Aquatic Hyphomycete Clavariopsis aquatica

Fungi are ecologically outstanding decomposers of lignocellulose. Fungal lignocellulose degradation is prominent in saprotrophic Ascomycota and Basidiomycota of the subkingdom Dikarya. Despite ascomycetes dominating the Dikarya inventory of aquatic environments, genome and transcriptome data relating to enzymes involved in lignocellulose decay remain limited to terrestrial representatives of these phyla. We sequenced the genome of an exclusively aquatic ascomycete (the aquatic hyphomycete Clavariopsis aquatica), documented the presence of genes for the modification of lignocellulose and its constituents, and compared differential gene expression between C. aquatica cultivated on lignocellulosic and sugar-rich substrates. We identified potential peroxidases, laccases, and cytochrome P450 monooxygenases, several of which were differentially expressed when experimentally grown on different substrates. Additionally, we found indications for the regulation of pathways for cellulose and hemicellulose degradation. Our results suggest that C. aquatica is able to modify lignin to some extent, detoxify aromatic lignin constituents, or both. Such characteristics would be expected to facilitate the use of carbohydrate components of lignocellulose as carbon and energy sources.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Divergent Metabolic Changes in Rhizomes of Lowland and Upland Switchgrass (Panicum virgatum) from Early Season through Dormancy Onset

High-biomass-yielding southerly adapted switchgrasses (Panicum virgatum L.) frequently suffer from unpredictable winter hardiness at more northerly sites arising from damage to rhizomes that prevent effective spring regrowth. Previously, changes occurring over the growing season in rhizomes sampled from a cold-adapted tetraploid upland cultivar, Summer, demonstrated a role for abscisic acid (ABA), starch accumulation, and transcriptional reprogramming as drivers of dormancy onset and potential keys to rhizome health during winter dormancy. Here, rhizome metabolism of a high-yielding southerly adapted tetraploid switchgrass cultivar, Kanlow—which is a significant source of genetics for yield improvement—was studied over a growing season at a northern site. Metabolite levels and transcript abundances were combined to develop physiological profiles accompanying greening through the onset of dormancy in Kanlow rhizomes. Next, comparisons of the data to rhizome metabolism occurring in the adapted upland cultivar Summer were performed. These data revealed both similarities as well as numerous differences in rhizome metabolism that were indicative of physiological adaptations unique to each cultivar. Similarities included elevated ABA levels and accumulation of starch in rhizomes during dormancy onset. Notable differences were observed in the accumulation of specific metabolites, the expression of genes encoding transcription factors, and several enzymes linked to primary metabolism.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Zymomonas mobilis oxidative stress transcriptomics

Transcriptomic analysis of WT, a deletion of ZMO_0422, and a deletion of ZMO_1411 in Zymomonas mobilis ZM4 under aerobic and anaerobic growth conditions along with various oxidative stresses: Paraquate addition, No Iron, and hydrogen peroxide addition.

aerobic↗
DOE OSTI2025

Zymomonas mobilis oxidative stress transcriptomics

Zymomonas mobilis is an important bioenergy organism that has potential to produce biofuels, including ethanol, in high volumes. Here we examined the response of Zymomonas mobilis to various oxidative stresses using genome-scale transcriptomics data. We first examined the transcrpit abundance in WT aerobic growth compared to aerobic grown in paraquat, which forms superoxide. Under anaerobic growth conditions we compared WT Zymomonas mobilis with strains grown in media lacking iron as well as strains lacking iron that were treated with the iron chelator DIP before collection. Finally we examined transcript abundance in cells lacking ZMO_0422 (Rrf2 family transcription factor homolog) and ZMO_1411 (Fur homolog) grown under anaerobic conditions. Overall design: Transcriptomic analysis of WT, a deletion of ZMO_0422, and a deletion of ZMO_1411 in Zymomonas mobilis ZM4 under aerobic and anaerobic growth conditions along with various oxidative stresses: Paraquate addition, No Iron, and hydrogen peroxide addition.

aerobic↗
DOE OSTI2025

Transcriptomic analysis of ZMO_0422 in Zymomonas mobilis

Deletion of the IscR homolog ZMO_0422 was performed in Zymomonas mobilis to investigate the role of Fe-S cluster biogenesis in Zymomonas. Here we perform genome-wide transcirptomics study to examine transcript chagnes in delta-ZMO_0422 compared to WT Zymomonas mobilis under both aerobic and anaerobic growth conditions. Overall design: Transcriptomic analysis of WT and a deletion of ZMO_0422 of Zymomonas mobilis ZM4 under aerobic and anaerobic growth conditions.

aerobic↗
NASA NTRSDate not supplied

Evaluation of Correction Methods for NASA GeneLab Transcriptomic Datasets

Conducting space biology experiments aboard the International Space Station, particularly those utilizing complex model organisms like mice, is expensive and difficult due to limited crew availability, hardware, and space. As a result, sample numbers from these studies are low, reducing the statistical power of any one experiment. Aggregating spaceflight datasets serves as a method to increase sample numbers, allowing for novel insights through bioinformatic analysis of ‘omics data from merged datasets. However, aggregating datasets can introduce unwanted variation including 1) differences in sample handling, processing, and sequencing platforms between datasets (technical variation) as well as 2) differences in experimental design between datasets such as sex or age of the model organism used. In the present study, NASA GeneLab-hosted RNAseq datasets from rodent liver tissues were used to evaluate several statistical methods to correct for this unwanted variation through two approaches, reference-based and standard. The following correction algorithms were applied with (reference-based) and/or without (standard) considering Universal Mouse RNA Reference samples: ComBat and ComBat_seq from the SVA package, median polish, empirical Bayes, and ANOVA-based algorithms from the MBatch package, and negative binomial regression normalization in the DESeq2 package. For each approach, after the correction algorithm was applied, differential gene expression (DGE) analysis of flight and ground control samples was performed with the combined data. The robustness of each tool was evaluated using BatchQC, to determine statistical differences between datasets before and after correction, Principal Component Analysis, to evaluate global gene expression in samples before and after correction, and by comparing DGE analysis of individual datasets and combined datasets before and after correction. The results showed that the reference-based approach introduced several additional (and likely artificial) DEGs when compared with the standard approach. Thus, the most robust standard correction will be implemented in the GeneLab Visualization 2.0 platform when datasets are combined.

GeneLab, RNA-seq, Batch Correction↗
NASA NTRSDate not supplied

Evaluation of Correction Methods for NASA GeneLab Transcriptomic Datasets

Conducting space biology experiments aboard the International Space Station, particularly those utilizing complex model organisms like mice, is expensive and difficult due to limited crew availability, hardware, and space. As a result, sample numbers from these studies are low, reducing the statistical power of any one experiment. Aggregating spaceflight datasets serves as a method to increase sample numbers, allowing for novel insights through bioinformatic analysis of ‘omics data from merged datasets. However, aggregating datasets can introduce unwanted variation including 1) differences in sample handling, processing, and sequencing platforms between datasets (technical variation) as well as 2) differences in experimental design between datasets. In the present study, NASA GeneLab-hosted RNAseq datasets from mouse liver tissues were used to evaluate several statistical methods to correct for this unwanted variation through two approaches, reference-based and standard. The following correction algorithms were applied with (reference-based) and/or without (standard) considering Universal Mouse RNA Reference samples: ComBat and ComBat_seq from the SVA package, median polish, empirical Bayes, and ANOVA-based algorithms from the MBatch package, and negative binomial regression normalization in the DESeq2 package. For each approach, after the correction algorithm was applied, differential gene expression (DGE) analysis of flight and ground control samples was performed with the combined data. The robustness of each tool was evaluated using BatchQC to determine statistical differences between datasets before and after correction, Principal Component Analysis to evaluate global gene expression in samples before and after correction, and by comparing DGE analysis of individual datasets and combined datasets before and after correction. The results showed that the reference-based approach introduced several additional (and likely artificial) DEGs when compared with the respective standard approach. Of the methods tested, standard ComBat and DESeq2 were identified as the most robust correction methods for combining spaceflight mouse liver RNAseq datasets hosted on GeneLab.

GeneLab↗